Scenario 2 : Carbon Constraint

The Model Description

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The carbon constrained scenarios seek to opportunistically charge the EVs at times of reduced grid carbon to mitigate the associated carbon footprint with charging. These models utilise historic grid carbon data from the National Grid Carbon API. The historic data sets are from 2019, and give carbon intensity values every half hour for the full year, as well as regional data from around the UK. The carbon constrained scenarios then use this data as a signal for when to charge the EVs, ie when the carbon values are at a minima for the desired time period. This carbon intensity signal is indicative of renewable energy generation and is therefore a method to attempt to maximise the quantity of renewable energy used to charge electric vehicles. 

Ideal Carbon Constraint

▪ All EV charging is reallocated to the time with minimum carbon in a 24 hour period

▪The ideal case illustrates the maximum possible carbon reduction by shifting all charging to a time of minimum grid intensity

Working Days Carbon Constraint

▪ Vehicles arriving within work hours are reallocated a charging time with the lowest carbon intensity from 10am-4pm

The model was altered to examine the demand profiles and carbon emission reductions that are possible due to opportunistically charging an EV at times of lower grid carbon. This was implemented for several regions utilising grid carbon intensity data for the UK, North Wales, and Scotland.

Ideal Carbon Constraint

The ideal carbon constrained scenario aims to the display the greatest theoretical reduction in emissions associated with charging, by reallocating all electric vehicle charging to the time with the minimum carbon intensity during a 24 hour period. While this scenario does not present a realistic situation, as this level of coordinated charging would be extremely impractical for both EV users and the grid, it allows us to set a benchmark for minimum possible emissions associated with charging.

Ideal Carbon Constraint Model Schematic

The schematic displays a simplified block diagram of the algorithm used to generate ideal carbon constrained charging demand. The initial steps are the same as other scenarios, with the probability of an EV charging on a given day and its state of charge being stochastic. Then if the EV is going to charge on the current day being simulated, the code checks through the historic carbon data for that day and finds the time with the minimum carbon intensity for that 24 hours period. This time is then set as the charging time for all electric vehicles. The model then executes the charging procedure for each electric vehicle, calculating the charging demand. The whole process is repeated for every electric vehicle in the input population (2000 EVs) determining whether they will charge, and if so, calculating their charging demand. , with the steps in the above diagram being repeated each day for the required period of time (1 year).

Ideal Carbon Tool Result

Figure 1, 1 Week of Ideal Carbon Constrained and Unconstrained  Charging Demand

Figure 1 displays a week of charging demand, including unconstrained charging demand generated from the base tool, as well as ideal carbon constrained demand proiles. The carbon constrained demand profiles are generated by implementing historic carbon data for three areas, Southern Scotland (yellow), North Wales (dark blue/grey) and carbon intensity averaged across the entire United Kingdom (cyan). 

Figure 2, 24 hour period of ideal carbon constrained and unconstrained charging

Figure 2 displays the first 24 hour period from figure 1. This displays a more detailed picture of how the charging demand is changing during a typical 24 hour period, when compared to unconstrained charging demand in black. This displays that not every region of the United Kingdom will experience a minimum value of grid carbon intensity at the same time, as the charging times for North Wales, South of Scotland and UK averged are staggered. This is to be expected, as each region will experience varying weather conditions, therefore varying levels of renewable energy generation. The most striking property of this altered demand graph is the major increase in peak charging demand as a result of reallocating all charging during a day to one time. 

Figure 3, (Right) Carbon Emissions associated with charging electric vehicles for both unconstrained charging (Basic) and Carbon constrained charging (Ideal), (Left) Comparison of peak charging demand for each scenario 

Figure 3 displays graphs of both the annual carbon footprint for each EV in both the ideal carbon constrained model and the unconstrained base model. It is apparent that altering the time during a 24 hour period that an EV will charge can reduce the EVs carbon footprint by utilising a greater quantity of renewable energy, however the actual magnitude of this carbon saving is low, with the maximum saving being 22kg of CO2 for EVs in North Wales. The graph on the right in figure three displays the maximum peak charging demand during the first week of the year for the ideal carbon constrained model, the time constrained model and the base unconstrained model. The slight variation in peak demand between the three ideal models is due to the stochastic nature of the model, which was accounted for in results generation by performing multiple runs of the model and averaging the results. 

Working Day Carbon Constraint

The working day carbon constraint seeks to reallocate all EV charging that would occur during a typical working day to the time with minimum grid carbon intensity during work hours. The working day carbon model utilises the assumption that the majority of EVs used for commuting and daily travel are required to be fully charged by 4pm at the latest. Additionally, the assumption is made that an EV can be present at a charger for the entire duration that it is parked in order for its charging time to be altered without user intervention (ie the EV driver moving their car to or from a charger). The working day scenario was selected as parking during this time follows more consistent and predictable behaviour than other times during the day, therefore we can more effectively make assumptions about how long an EV could be present at a charger in order to automatically change its charging time. 

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Working Day Carbon Constraint Model Schematic

This schematic displays the same steps as previous schematics for determining whether an EV will charge on a given day. It then checks the implemented 2019 historic grid carbon data (for the UK, Southern Scotland or North Wales), to determine the most opportune time to charge cars during the working day 8am - 5pm, then reallocates all cars that would charge during this time period to the time with minimum grid carbon. All EVs arriving outside this time period are allowed to charge without any form of constraint as they fall outwith time periods with easily predictable parking behaviour.

Working Day Carbon Tool Result